The Purpose of This Independent Project

  • To help my friend narrow down what dog breed to get.

Consider Your Lifestyle

  • How active are you?
  • Do you have children?
  • Do you have the necessary funds?
  • Do you have the time to train them?
  • Are you home for long periods?
  • What will you do with the dog when your out of town?

Consider Your Expectations

  • Do you prefer large or small dogs?
  • How much time are you willing to spend grooming a dog? Do you have allergies?
  • Do you have a specific activity you want the dog to do with you?

Breed Groups

  1. Working - Bred for practical duties like watchdogs and sled dogs. They are intelligent and loyal.
  2. Herding - Bred to herd livestock and are smart and energetic.
  3. Hound - Bred for hunting. They are affectionate and strong- willed.
  4. Sporting - Bred to retrieve game. They have high energy levels.
  5. Non-Sporting - Dogs who don’t fit into any other category.
  6. Toy - Bred to be companions.
  7. Terrier - Bred to kill vermin.

Character Traits

  1. Adaptability Level
  2. Affectionate With Family
  3. Barking Level
  4. Coat Grooming Frequency
  5. Drooling Level
  6. Energy Level
  7. Good With Other Dogs
  8. Good With Young Children
  9. Mental Stimulation Needs
  10. Openness To Strangers
  11. Playfulness Level
  12. Shedding Level
  13. Trainability Level
  14. Watchdog/Protective Nature

Load the Libraries

library(plotly)
library(here)
library(tidyverse)
library(ggplot2)
library(dplyr)
library(magick)
library(rmdformats)

Read in the Data

Breed_Traits <- read_csv(here("Data","Breed Traits.csv")) # Load first data set

View(Breed_Traits)


AKC_Breed_Info <- read_csv(here("Data","AKC Breed Info.csv")) # Load second data set 

View(AKC_Breed_Info)

Breed Groups vs. Traits

Pivot Data Long

long <- Breed_Traits %>%
 pivot_longer(cols = c(`Affectionate With Family`,`Good With Young Children`, `Good With Other Dogs`, `Shedding Level`, `Coat Grooming Frequency`, `Drooling Level`, `Openness To Strangers`, `Playfulness Level`, `Watchdog/Protective Nature`, `Adaptability Level`, `Trainability Level`, `Energy Level`, `Barking Level`, `Mental Stimulation Needs`), # variables in the new column
              names_to = 'Traits', # new name of the column
              values_to = 'Values') # name of the column 
View(long)

Create Bar Plot: Character traits measured by Breed Group

Traits_long <- long %>% # graph with this data 
  plot_ly(x = ~ `Breed Group`, 
          y = ~ Values,
          color = ~ Traits,
          type = "bar", # bar graph 
          marker = list(color = rainbow(nrow(long)))) %>% # bar graph is colored by rainbow
  layout(title = 'Breed vs. Traits', # add a title 
         xanchor = 'center', # center the title 
          yanchor = 'top',
         font = list(color = "darkorchid"), # change title color 
       plot_bgcolor = "white", # made background white
       paper_bgcolor = "lavender", # paper background color
       xaxis = list(title = 'Breed Group', # label x axis
                    tickangle = -45, # angle the x axis 
                    color = "darkorchid", # color x axis
                      size = 15),# make the x axis smaller 
       yaxis = list(title = 'Rank', # label y axis 
                    color = "darkorchid"), # color of y axis title 
       legend = list(title = list(text = '<b> Traits </b>', # rename legend 
                        font = list(color = "darkorchid"), # change legend color 
                                  xanchor = 'center', # center the legend
                                  yanchor = 'top')))



Traits_long

Narrow Down By Coat Type and Length

Filter Data To Visualize Coat Length

coat_filtered <- Breed_Traits %>%
  filter(`Breed Group` %in% c("Hound","Sporting")) %>% # filter out breed group
  filter(`Coat Type` %in% c("Smooth","Double")) %>%# filter out coat preference
  filter(`Affectionate With Family` >= 3)%>%
  filter(`Good With Other Dogs` >= 3) %>%
  filter(`Trainability Level` >=3) %>%
  filter(`Adaptability Level` >=3) %>%
  filter(`Coat Length` == "Short")
  
  
  
  
View(coat_filtered)

Table: Coat Type for Certain Breeds

table <- coat_filtered %>%
plot_ly(
  type = 'table',
  columnwidth = c(80),
  header = list(
    values = c('<b>Breed</b>','<b>Affectionate With Family</b>','<b>Good With Other Dogs</b>','<b>Adaptability Level</b>','<b>Trainability Level</b>','<b>Coat Type</b>','<b>Coat Length</b>'),
    line = list(color = '#506784'),
    fill = list(color = '#119DFF'),
    align = c('left','center'),
    font = list(color = 'white', size = 12)
  ),
  cells = list(
    values = rbind(
      c('Retrievers (Labrador)', 'Beagles', 'Pointers (German Shorthaired)', 'Dachshunds', 'Brittanys','Vizslas','Basset Hounds','Weimaraners','Rhodesian Ridgebacks','Bloodhounds','Whippets','Pointers','Black and Tan Coonhounds
','Bluetick Coonhounds','Greyhounds','Salukis','Redbone Coonhounds','Treeing Walker Coonhounds','Cirnechi dell’Etna','Pharaoh Hounds','American English Coonhounds','Sloughis','Harriers','American Foxhounds','English Foxhounds'),
      c(5,3,5,5,3,5,3,5,5,4,5,5,4,3,4,5,5,5,4,5,3,4,5,3,5),
      c(3,3,3,3,3,4,4,4,4,4,4,5,5,5,5,5,5,5,5,5,5,5,5,5,5),
      c(4,4,3,3,3,4,4,3,5,4,4,5,4,3,3,4,4,3,4,4,3,3,4,3,4),
      c(5,4,4,3,3,5,4,5,5,3,4,5,3,3,3,5,3,4,3,5,4,3,4,3,4),
      c("Smooth","Smooth","Smooth","Smooth","Smooth","Smooth","Smooth","Double","Smooth","Smooth","Smooth","Double","Smooth","Smooth","Smooth","Smooth","Smooth","Smooth","Smooth","Smooth","Smooth","Smooth","Double","Smooth","Double"),
      c("Short","Short","Short","Short","Short","Short","Short","Short","Short","Short","Short","Short","Short","Short","Short","Short","Short","Short","Short","Short","Short","Short","Short","Short","Short")),
    line = list(color = '#506784'),
    fill = list(color = c('#25FEFD', 'white')),
    align = c('left', 'center'),
    font = list(color = c('#506784'), size = 12)
    ))
table

Narrow Down By Weight

Filter Data To Visualize Weight

weight_f <- AKC_Breed_Info %>%
  drop_na() %>%
  filter(Breed %in% c("Whippet","Vizsla","Rhodesian Ridgeback","Labrador Retriever","German Shorthaired Pointer","Pharaoh Hound","Harrier","English Foxhound","Black And Tan Coonhound","Basset Hound","Beagle","Dachshund","Brittany","Weimarener","Bloodhound","Whippet","Basenji","Pointer","Greyhound","Redbone Coonhound")) %>% # filter data to be universal 
  filter(weight_low_lbs >= 45) %>% # look at weights greater than 45 lbs
  filter(weight_high_lbs <= 100) # weight less than 100 lbs
  
  

View(weight_f)

Scatter Plot: Weight for Certain Breeds

weight <- weight_f %>% # plot filtered data 
  plot_ly(x = ~ weight_low_lbs,
          y = ~weight_high_lbs,
          type = "scatter", # type of data
          mode = "markers",
          color = ~Breed, # color by
          colors = "Paired", # color pattern
          size = 22, # size of dot
          alpha = 1) %>%
layout(title = 'Breed vs. Weight', # title of plot
         font = list(color = "navy"), # title color 
       plot_bgcolor = "white",# plot color 
       paper_bgcolor = "lightcyan", # background color 
       xaxis = list(title = 'Low Weight Range', # x axis title 
                    tickangle = -45, # angle x axis 
                    color = "navy"), # color x axis
       yaxis = list(title = 'High Weight Range', # y axis title 
                    color = "navy"), # y axis color 
       legend = list(title = list(text = '<b> Breed </b>', # legend title 
                                  font = list(color = "navy"), # legend color 
                                  xanchor = 'center', # center title 
                                  yanchor = 'top')))

weight

Narrow Down By Height

Filter Data Based on Height

height_f <- weight_f %>%
  filter(height_low_inches >= 21) %>% 
  filter(height_high_inches <= 26)

View(height_f)

Scatter Plot: Weight for Certain Breeds

height <- height_f%>% # plot filtered data 
  plot_ly(x = ~ height_low_inches,
          y = ~height_high_inches,
          type = "scatter", # type of data
          mode = "markers",
          color = ~Breed, # color by
          colors = "Paired", # color pattern
          size = 22, # size of dot
          alpha = 1) %>%
layout(title = 'Breed vs. Height', # title of plot
         font = list(color = "navy"), # title color 
       plot_bgcolor = "white",# plot color 
       paper_bgcolor = "lightcyan", # background color 
       xaxis = list(title = 'Low Height Range', # x axis title 
                    tickangle = -45, # angle x axis 
                    color = "navy"), # color x axis
       yaxis = list(title = 'High Height Range', # y axis title 
                    color = "navy"), # y axis color 
       legend = list(title = list(text = '<b> Breed </b>', # legend title 
                                  font = list(color = "navy"), # legend color 
                                  xanchor = 'center', # center title 
                                  yanchor = 'top')))
height

One Last Comparison

Filter Data For 4 Categories

trait_filter <- long %>%
  filter(Breed %in% c("English Foxhounds","Retrievers (Labrador)","Pharaoh Hounds","Vizslas")) %>%
  filter(Traits %in% c("Trainability Level","Adaptability Level","Good With Other Dogs","Affectionate With Family"))

View(trait_filter)

Bar Plot: Final Filtered Breeds by Adaptability, Trainability, Good With Other Dogs, and Affectionate With Family

final <- trait_filter %>% # data used
  plot_ly(x = ~ Traits,
          y = ~Values,
          type = "bar", # type of graph 
          mode = "markers",
          color = ~Breed, # color by
          colors = "Dark2") %>% # color pattern
  layout(title = 'Vizsla vs. Greyhounds', # plot title
         font = list(color = "darkred"), # title color 
       plot_bgcolor = "bisque", # color of plot
       paper_bgcolor = "bisque", # color of background
       xaxis = list(title = 'Traits', # x axis title 
                    tickangle = -45, # angle x axis 
                    color = "darkred"), # x axis color
       yaxis = list(title = 'Rank',# y axis title
                    color = "darkred"), # y axis color
       legend = list(title = list(text = '<b> Breed </b>', # legend title
              font = list(color = "darkred"), # legend color
                      xanchor = 'center', # title centered 
                      yanchor = 'top')))


final

Image of The Winner

Image of The Winner

Vizsla <- image_read("https://images.ctfassets.net/m5ehn3s5t7ec/wp-image-198422/0e0fe308ed17ab3af5f3c8f2db288667/Vizsla-Dog-Breed-Information.jpg") # read in image

image_border(Vizsla, color = "peachpuff", 
             geometry = "8x10") %>% # Add a border
image_annotate("Vizsla", font = 'Palatino',
               size = 50, 
               gravity = "southwest",
               color = "black", 
               boxcolor = "peachpuff") # add text box

# References